Document Indexing Framework for Retrieval of Degraded Document Images

With the availability of large collection of document images in Indian languages, image based retrieval has gained popularity. The performance of such systems is effected by the presence of degraded and noisy images. Moreover, Optical character recognition systems for Indian scripts are not yet robust, leading to noisy OCR'ed text. Information retrieval system designed using inputs from both modalities (image features and OCR based recognition data) will lead to better retrieval performance in contrast to usage of individual modality. In this paper we present a indexing methodology that uses multiple kernel learning to combine features from different modalities by joint optimization of search time and accuracy. The evaluation of the proposed methodology is demonstrated on document images of Bangla and Devanagari script.